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ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan
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The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and the development of countermeasures. ASVspoof 2021 is the 4th in a series of bi-annual, competitive challenges where the goal is to develop countermeasures capable of discriminating between bona fide and spoofed or deepfake speech. This document provides a technical description of the ASVspoof 2021 challenge, including details of training, development and evaluation data, metrics, baselines, evaluation rules, submission procedures and the schedule.
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Cited by 2 Pith papers
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SONAR: Spectral-Contrastive Audio Residuals for Generalizable Deepfake Detection
SONAR improves audio deepfake detection by explicitly aligning low- and high-frequency representations for real speech and repelling them for fakes, setting new benchmark EERs on ASVspoof 2021 and in-the-wild data.
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RoVo: Robust Voice Protection Against Unauthorized Speech Synthesis with Embedding-Level Perturbations
RoVo perturbs BARK codec embeddings instead of raw audio, and reports that speech-synthesis clones of protected voices are rejected by speaker verification 70+ percentage points more often, with better robustness to s...
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